Institute small-business-payroll-report

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The Ups and Downs of
Small Business Employment
Big Data on Payroll Growth and Volatility
January 2017

About the Institute
The global economy has never been more complex, more interconnected, or faster moving. Yet economists,
businesses, nonprofit leaders, and policy makers have lacked access to real-time data and the analytic tools to
provide a comprehensive perspective. The results—made painfully clear by the Global Financial Crisis and its
aftermath—have been unrealized potential, inequitable growth, and preventable market failures.
The JPMorgan Chase Institute is harnessing the scale and scope of one of the world’s leading firms to explain the
global economy as it truly exists. Its mission is to help decision-makers—policymakers, businesses, and nonprofit
leaders—appreciate the scale, granularity, diversity, and interconnectedness of the global economic system and use
better facts, timely data, and thoughtful analysis to make smarter decisions to advance global prosperity. Drawing
on JPMorgan Chase’s unique proprietary data, expertise, and market access, the Institute develops analyses and
insights on the inner workings of the global economy, frames critical problems, and convenes stakeholders and
leading thinkers.
The JPMorgan Chase Institute is a global think tank dedicated to delivering data-rich analyses and expert insights
for the public good.
Acknowledgments
We thank our research team, including Derek Bekebrede and Andreas Weber, for their hard work and contribution to this report.
We would like to acknowledge Jamie Dimon, CEO of JPMorgan Chase & Co., for his vision and leadership in establishing the Institute
and enabling the ongoing research agenda. Along with support from across the firm—notably from Peter Scher, Len Laufer, Max
Neukirchen, Joyce Chang, Matt Zames, Judy Miller, and Alexis Bataillon—the Institute has had the resources and support to pioneer
a new approach to contribute to global economic analysis and insight.
We would also like to acknowledge the contribution of our other researchers, specifically Kanav Bhagat, Chenna Cotla, Fiona Greig,
Drew Pinta, Jessica Wu, Kerry Zhang and Chen Zhao. We especially want to thank Jenn Piepszak and the Chase Business Banking
team for their support, and other experts within JPMorgan Chase, including Bori Cox, Sally Durdan, Brian Haney, Anmol Karnad,
Adam Nelson, Brent Reinhard, Mary Jane Rogers, Sam Saperstein, and David Spyra. This effort would not have been possible without
the critical support of the JPMorgan Chase Intelligent Solutions team of data experts, including Joe Bimmerle, Steve Farrell, Jay
Galloway, Shannon Kim, Stella Ng, Michael Solovay, and Tony Wimmer, and JPMorgan Chase Institute team members Kelly Benoit,
Kathryn Kulp, Natalie Holmes, and Gena Stern.
Finally, we would like to acknowledge with gratitude the invaluable input of small business experts who provided thoughtful
commentary, including John Haltiwanger, Brian Headd, Ron Jarmin, Raymond Keating, Kausar Hamdani, Nick Maduros, Claire
Kramer Mills, Karen Mills, Jonathan Parker, Arthur Plews, and Scott Shane. For their generosity of time, insight, and support, we
are deeply grateful.

The Ups and Downs of
Small Business Employment
Big Data on Payroll Growth and Volatility
Diana Farrell
Chris Wheat
Contents
2 Executive Summary
8 Findings
21 Conclusion and Implications
23 Data Asset
27 Methodology
29 Appendix
31 References
32 Endnotes

2
Data
Selected key industries
Core metropolitan employer businesses
Small businesses
For at least five of nine months, at least $500 in outflows
and 10 transactions
$500+
1+
We define core businesses as those businesses that have financial activity
that indicates they are not seasonal businesses, hobby businesses, small
office/home office businesses (SOHOs), micro businesses, etc.
The businesses we study are part of 12 selected key industries
that comprise key elements of the small business sector:
Together, these 12 industries capture 73 percent of for-profit
employer small firms and 65 percent of for-profit small
business employment.
Other Professional
Services
Metal & Machinery
Real Estate
Personal Services
Retail
Wholesalers
Construction
Health Care
Services
High-Tech
Manufacturing
High-Tech Services Restaurants
Repair &
Maintenance
<
$20m
At least one and fewer than 500 employees in each payroll period
Are located in Metropolitan Areas where Chase has a
representative footprint
At least one inflow and outflow in each month
End-of-day combined balances do not exceed $20 million each day
Hold Chase Business Banking accounts
Do not identify with more than a single address and/or a
single industry
$
Executive Summary
Small businesses, defined as businesses with fewer than 500 employees, play a critical role in the US economy. They
provide work for nearly half (48 percent) of all employees in the US and are credited with creating 52 percent of net
job growth.1
Small businesses also account for a significant share of personal income, given their average annual
payroll of $45,000 per employee. Despite its importance, relatively little is known about the underlying dynamics of
employment growth and volatility at the individual small business level. In particular, publicly available aggregate
data provide an incomplete view of the ways in which employment in the sector shapes the financial well-being of
small business owners and their employees.
As part of a broader research agenda on the small business sector, the JPMorgan Chase Institute constructed a
sample of over 45,000 small business customers that had electronic payroll outflows for each of the nine non-holiday
months of 2015. These individual small business payroll outflows provide an important lens on the contributions
of small business sector employment to the US economy. Many public data sources that speak to the contribution
of employment from the small business sector only provide data on job counts often measured only once per year.
While payroll outflows are driven in part by job counts, they also provide a more granular and high-frequency view
of employment and wages. Our unique dataset provides a granular view of payroll growth and volatility and their
impact on employment at the individual business level.
We created a sample of 45,260 small businesses who hold Chase Business Banking deposit accounts and
meet our criteria for small, core metropolitan employer businesses. We then used their combined 65 million
transactions to produce a view of daily cash inflows, payroll and other cash outflows, and end-of-day balances
over the nine non-holiday months from February 2015 to October 2015.

3
THE UPS AND DOWNS OF SMALL BUSINESS EMPLOYMENT
Executive Summary
Note: We calculated annual full-time equivalent (FTE) wages for a firm by dividing the total annual payroll for its 6-digit NAICS industry by the total number of
employees in that industry. We identify FTE changes by comparing annualized payroll growth to this annual FTE wage measure. Annual payroll and employee data are
from the US Census Statistics of US Businesses.
Lost more than 1 FTE Lost less than 1 FTE Gained less than 1 FTE Gained 1 to 2 FTEs Gained more than 2 FTEs
Losses in FTEs Gains in FTEs
11.4%
TO
20.4%
OR
MORE
15.5%
OR
MORE
21.0%
31.7%
Shareofsmallemployerbusinesses
Distribution of annualized payroll growth
-95% 0% 95% 195%
0%
1%
2%
3%
4%
5%
6%
7%
8%
9%
Annualized payroll growth
8.5%
Payroll Growth
Finding
One
Payroll for most small employer businesses grew by less than the equivalent
of one full-time employee in a calendar year, with median annualized payroll
growth of 8.5 percent.
Monthly payroll payments from the
median small employer business in our
sample grew at an annualized rate of
8.5 percent per year. This growth rate
corresponded to the addition of less
than one full-time equivalent (FTE).
Moreover, 36.5 percent of these firms
experienced declining payroll outflows,
consistent with the loss of at least a
partial FTE. In contrast, 31.8 percent of
small businesses experienced growth
in payroll outflows consistent with
the addition of one or more FTEs.

4
Executive Summary
Finding
Two
Payroll expenses were a material outflow for employer small businesses,
which held fewer cash buffer days than nonemployer small businesses.
Large payroll outflows can pose significant challenges to
small businesses with limited liquidity. We found that across
employers and nonemployers, the typical small business
only carried 27 cash buffer days. Moreover, the typical
employer small business had only 18 cash buffer days,
significantly fewer than 27. The size and volatility of payroll
expenses may put substantial stress on the relatively
limited cash reserves of these employer small businesses.
Employer
small business
payroll share
of outﬂows
18%
($18,700)
35 DAYS
62 DAYS
9 DAYS
13 DAYS
18 DAYS
27 DAYS
Employer small businesses
All small businesses
25th
percentile 75th
percentileMedian
25th
percentile 75th
percentileMedian
Cash buffer days are the number of
days of cash outflows a business could
pay out of its cash balance if its inflows
were to stop. We estimate cash buffer
days for a business by computing the
ratio of its average daily cash balances
to its average daily cash outflows.
The typical employer small business had payroll outflows of $18,700, or 18 percent of all outflows.

5
Executive Summary
Finding
Three
Most small employer businesses experienced unstable payroll and employment
volatility including job gains and losses and other spikes and dips in payroll.
Small changes
Businesses with small
changes only experience
payroll changes that are
less than hiring or ﬁring
one employee.
61.8%38.2%
Share of employer small businesses
Stable payroll Unstable payroll
BONUS
PAST DUE
Spikes and/or dips
Businesses with spikes or
dips have at least one
instance of a large change
in payroll that is quickly
reversed. These businesses
can also experience small
changes and sustained
gains and losses.
Sustained gains
and/or losses
Businesses with sustained
gains appear to be steadily
hiring new employees and
growing their workforce.
Those with sustained
losses appear to be losing
employees and shrinking
their workforce.
61.8% of small employer businesses experienced unstable sustained gains and/or losses, spikes,
dips, or spikes and dips.

6
Executive Summary
LOW VOLATILITY
Small changes
25 percent of small businesses
experienced payroll changes no
more volatile than the small
changes pattern.
HIGH VOLATILITY
Spikes and dips
25 percent of small businesses
experienced payroll changes at
least as volatile as the spikes
and dips pattern.
FTEs
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
0
1
2
3
4
5
6
Small change (<1 FTE) Large change (1+ FTE)
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
0
1
2
3
4
5
6
FTEs
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
0
1
2
3
4
5
6
FTEs
TYPICAL
VOLATILITY
Gains and losses
Most small businesses experienced
payroll changes similar to the gains
and losses pattern.
While small business payroll grew by less than the equivalent of one FTE over the course of a year, growth
was rarely smooth.
Finding
Four
The typical small employer business experienced substantial volatility in payroll
outflows, and volatility was highest for younger small employer businesses.

7
Executive Summary
Median cash buffer days by payroll volatility type
15 DAYS
16 DAYS
16 DAYS
17 DAYS
17 DAYS
18 DAYS
19 DAYS
20 DAYS
Dips
Combined sustained
gains and losses
Sustained gains
Both spikes
and dips
Sustained losses
All employer
small businesses
Small changes
Spikes
The median small employer business with dips, combined sustained gains and losses, and sustained
gains had the fewest cash buffer days.
• Small employer businesses with spikes were one exception to this rule, which may reflect businesses that pay
bonuses or commissions with growing revenues
Finding
Five
Small employer businesses with more volatile payroll patterns tended to
have fewer cash buffer days.
Conclusion
The findings in this report are relevant for policy makers, advocates, and private-sector partners alike.
These findings suggest that those who seek to help small businesses should focus not only on new business
creation but specifically on minimizing payroll volatility, which can benefit both small business owners
and employees. Moreover, they shed light on trade-offs inherent in policies that improve wages of small
business employees but impose costs on small business owners.

8
Findings
Finding
One
Payroll for most small employer businesses grew by less than the equivalent
of one full-time employee in a calendar year, with median annualized payroll
growth of 8.5 percent.
Payroll growth can be a sign of a healthy business that is growing, providing increasing income for its employees, and potentially
increasing the economic well-being of its owners. In contrast, declining payroll can be a sign that a small business is facing an
economic downturn and eliminating jobs.
The median small employer business in our sample had payroll growth of 8.5 percent on an annualized basis, with wide variation
in payroll growth across all businesses, as shown in Figure 1. At the lower end, 25 percent of small employer businesses had payroll
that contracted at a rate greater than 10 percent, while on the upper end, 25 percent of small employer businesses had payroll that
grew at a rate of greater than 42.9 percent. Moreover, we found that 13 percent of our sample had payroll that more than doubled
during 2015.
Figure 1: Payroll Grows at 8.5 percent per Year in the Median Small Employer Business
25th percentile:
-10.0%
Median:
8.5%
75th percentile:
42.9%
Distribution of annualized payroll growth
-95%
-85%
-75%
-65%
-55%
-45%
-35%
-25%
-15%
-5%
5%
15%
25%
35%
45%
55%
65%
75%
85%
95%
105%
115%
125%
135%
145%
155%
165%
175%
185%
195%
0%
1%
2%
3%
4%
5%
6%
7%
8%
9%
Annualized payroll growth Source: JPMorgan Chase Institute

Findings
9
To relate this wide range of payroll growth rates to employment changes, we converted changes in dollars of payroll outflow to
changes in full-time equivalents (FTEs). To do this conversion, we first estimated the typical monthly payment associated with an
FTE in a given industry.2
This allowed us to estimate the number of employees for each firm at the beginning of our time window in
February and at the end of our window in October. We used these observations to estimate the number of additional FTEs each firm
would have hired (or lost) in a full calendar year. For example, an increase in payroll of 10 percent could correspond to two new full-
time jobs for a small firm with 20 employees, while corresponding to a part-time employee or an increase in hours for a small firm
with 5 employees. Figure 2 presents the distribution of these changes for the firms in our sample.
Figure 2: Most Small Employer Businesses Gained Less than a Full-Time Equivalent in a Year
Source: JPMorgan Chase Institute
Shareofemployersmallbusinesses
Share of annualized job gain rates
15.5%
21.0%
31.7%
11.4%
20.4%
Lost More than 1 FTE Lost Less than 1 FTE Gained Less than 1 FTE Gained 1 to 2 FTEs Gained More than 2 FTEs
Estimated annual FTE growth
Losses in FTEs Gains in FTEs
Across all firms in our sample, 36.5 percent of firms experienced declining payroll outflows, consistent with partial or full job
reductions, including 15.5 percent that lost more than an FTE. An additional 31.7 percent experienced payroll growth consistent with
less than one full-time hire. In total, most of the small employer businesses—68.2 percent—either lost jobs or added less than a single
job in a calendar year. Some firms do experience more significant job growth—11.4 percent of firms saw increases consistent with one
to two new employees, and 20.4 percent of firms saw increases consistent with two or more new employees.3

Findings
10
Payroll growth of younger firms
Notably, we also found that the payroll outflows of younger firms grow more quickly than those of older firms, particularly in their
first two years. Figure 3 displays the median annualized payroll outflow growth rate by the age of the business.4
In our sample, firms
less than two years old experienced payroll growth substantially higher than those older than two years.The median firm in its first
year saw payroll outflows grow at an annualized rate of 15.1 percent, while the median firm in its second year saw payroll grow at
12.7 percent per year. Older firms saw decidedly lower growth rates—the median 10-year-old firm only saw payroll outflows grow at
6.3 percent per year.
Figure 3: Payroll Growth is Strongest in the First Two Years
Medianannualizedgrowth
Median annualized payroll growth by age15.1%
12.7%
9.3%
8.6%
9.8%
10.4%
8.9%
7.9%
5.8%
7.1%
6.3%
<1 year 1 year 2 years 3 years 4 years 5 years 6 years 7 years 8 years 9 years 10 years
Age in years
The high payroll growth we observed among young firms potentially sheds light on an often underreported characteristic of small
business employment—the net job loss among existing small businesses. Small businesses are frequently noted for their contribution
to net job creation (Birch, 1981). However, recent scholarship has highlighted the importance of new rather than small businesses
in creating US jobs (Haltiwanger, et al., 2013). By definition, all newly founded businesses create jobs—all newly founded firms
had no employees in the prior year. In contrast, data from the US Census show that job losses from small businesses that exit
(cease operations) exceed job creation by existing small businesses. Figure 4 illustrates the contributions of new and existing small
businesses to job creation from March 12, 2013 to March 12, 2014.

Findings
11
Figure 4: While All Small Firms Added Net Jobs, Existing Small Firms Lost Net Jobs in 2013
Job creation by
existing firms
Jobs at firms
with 5 to 9
employees
Job creation
by new firms
Job loss from
firms exiting
Sample of
100
jobs in 2013
102.8
jobs
101.7
jobs in 2014
96.1
jobs
1.7%
increase in jobs
at all firms
3.9%
decline in jobs
at existing firms
2.8
jobs gained
5.6
jobs gained
6.7
jobs lost
Source: US Census Bureau
In order to map most closely to the median-sized firm in our sample, we focus our analysis on the universe of small firms with five to
nine employees. Small firms of this size that survived from 2013 to 2014 did, in fact, create jobs. These firms created 2.8 new net jobs
for every 100 employees—a positive growth rate consistent with the positive growth rate of payroll we observe among the firms that
survive the nine months of our study. However, those firms that did not survive the full year were responsible for 6.7 lost jobs. After a
year, only 96.1 employees were still employed by the small firms that existed at the beginning of
the year, a net loss of 3.9 jobs. In contrast, newly founded small firms created 5.6 jobs for
each of the original 100 employees. In combination, this produced 101.7 employees at
small firms for every 100 employees of the original firms, or a 1.7 percent net gain
in jobs. Notably, larger firms with 500 or more employees also created net jobs,
even excluding jobs created by new large firms.5
This result sheds light on the fragility of job growth for smaller businesses.
While new small businesses drive positive job creation for the sector as
a whole, existing small businesses lose net jobs because of firm failure.
Existing data provide a clear view of the jobs added or lost by these firms
from one year to the next, but little insight into the process during the
intervening months that may have contributed to their fragility. Findings 3
through 5 offer a view of high-frequency payroll variation to better inform
this process.
While new small
businesses drive positive
job creation, existing small
businesses lose net jobs
because of firm failure.

Findings
12
Cash flows related to employment expenses were a major component of overall cash flow for these small employer businesses, with
heterogeneity across industries, as shown in Figure 5. The typical small business in our sample had $18,700 in payroll expenses.
Payroll outflows varied from a median of $11,700 per month in the Restaurant industry to a median of $36,600 per month in the
High-Tech Services industry.
Figure 5: Median Monthly Payroll Outflows Vary Widely by Industry
Medianmonthlyoutﬂow
Median monthly payroll outﬂow by industry
$11,700 $12,700
$13,500
$14,500
$18,700
$19,900 $20,200 $20,500
$22,000
$23,300
$32,200
$33,200
$36,600
Restaurants
Personal
Services
Retail
Repair&
Maintenance
RealEstate
HealthCare
Services
Construction
OtherProfessional
Services
Wholesalers
High-Tech
Manufacturing
Metal&
Machinery
High-Tech
Services
AllSmall
Employer
Businesses
These payroll expenses comprised a significant fraction of the total outflows we observe among small employer businesses over the
non-holiday months of 2015, as illustrated in Figure 6. For the median small employer business in our sample, payroll comprised
18 percent of observed outflows. This percentage varies substantially across industries—payroll only comprised 10 percent of the
outflows of wholesalers and retailers, but 27 percent of the outflows of High-Tech Services firms.
Finding
Two
Payroll expenses were a material outflow for small employer businesses,
which held fewer cash buffer days than nonemployer small businesses.

Findings
13
Figure 6: Payroll as a Share of Outflows Varies Widely by Industry
Restaurants
Personal
Services
Retail
Repair&
Maintenance
AllSmall
Employer
Businesses
RealEstate
HealthCare
Services
Construction
OtherProfessional
Services
Wholesalers
High-Tech
Manufacturing
Metal&
Machinery
High-Tech
Services
Medianpayrollshareofoutflows
Median payroll share of outflows by industry
10.2% 10.2%
10.9%
13.5%
16.3% 16.4% 17.3%
17.8% 18.7%
20.8%
24.3% 24.4%
26.8%
Notably, our window on payroll outflows only captures the cash flows that correspond to small business employee take-home pay.
We also examined a subset of employers in our sample for which we could observe electronic payments for both take-home pay
and employment-related taxes. For these employers, tax payment outflows were an additional 23.1 percent of take-home pay. This
suggests that the full set of employment-related expenses including wage and tax payments was likely 22 percent of outflows for the
median employer and over 30 percent in industries such as Personal Services, Health Care Services, and High-Tech Services.
To the extent that these large payroll outflows are volatile, they could pose significant challenges to small businesses with limited
liquidity.InCashisKing:Flows,Balances,andBufferDays,wefoundthatacrossallsmallbusinesses(bothemployersandnonemployers),
the typical small business in the US only holds balances equivalent to 27 cash buffer days. In other words, these businesses carried
a cash balance only large enough to sustain 27 days of cash outflows if their inflows were to cease (Farrell and Wheat, 2016). As
Figure 7 shows, employer small businesses are likely to have even smaller cash buffers than nonemployer small businesses—the
median employer small business only held 18 cash buffer days. Employment is a major expense for many small businesses, so payroll
volatility may put substantial stress on limited cash reserves.
Figure 7: Employer Small Businesses Have Smaller Cash Buffers
Note: Cash buffer days are the number of days of cash outflows a business could pay out of its cash balance if its inflows were to stop. We estimate cash buffer days for a business by
computing the ratio of its average daily cash balance to its average daily cash outflows.
Cash buffer days
Cash buffer days by employer status
35 DAYS
62 DAYS
9 DAYS
13 DAYS
18 DAYS
27 DAYS
Employer
small
businesses
All small
businesses
0 10 20 30 40 50 60 70 80
25th
percentile
75th
percentileMedian

Findings
14
Finding
Three
Most small employer businesses experienced unstable payroll and
employment volatility, including job gains and losses and other spikes
and dips in payroll.
Volatile changes in payroll can adversely affect a small business. All else equal, a small
business that experiences a given level of average payroll growth is likely more able to
manage that growth if it occurs in smooth predictable increments than if it achieves
that same growth in widely variant changes over time.
In order to make the underlying growth and volatility in the payroll of small businesses
concrete, we first explore seven distinct patterns of payroll volatility. These patterns
are based on our analyses of FTE-level changes in month-to-month payroll outflows
described in the previous finding. Specifically, we first categorize changes in payroll
as small (less than one FTE) or large (greater than one FTE) and then identify specific
sequences of month-to-month changes in payroll outflows that map to qualitatively
different types of payroll volatility.
First, we consider firms that have no month-to-month absolute changes in payroll
outflow larger than one FTE, as illustrated in Figure 8.6
In each month, payroll
for this hypothetical firm changes by less than the average monthly payroll per
employee for firms in its industry. A small business that grows or shrinks its
workforce principally through part-time hires, that increases or decreases the
hours of its existing employees, or that increases or decreases the wages of its
employees would show this pattern of outflows.7
Figure 9: Illustrative Examples of Sustained Gains and Losses
Note: We define a full-time equivalent (FTE) as a payroll outflow equivalent to the mean monthly wages per employee for small firms in the same 6-digit NAICS industry as a firm
in our sample.
FTEs
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
0
1
2
3
4
5
6
Sustained gains2 3 4
FTEs
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
0
1
2
3
4
5
6
Sustained losses
FTEs
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
0
1
2
3
4
5
6
Gains and losses
Figure 8: Illustrative Example of
Small Changes
Note: We define a full-time equivalent (FTE) as a
payroll outflow equivalent to the mean monthly
wages per employee for small firms in the same
6-digit NAICS industry as a firm in our sample.
FTEs
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
0
1
2
3
4
5
6
Small changes1

Findings
15
All other firms had at least one month in which payroll changed by more than one FTE from the prior month. Of these, we first
consider firms that have a change in payroll greater than one FTE in one month that sustain the gain or loss for at least one additional
month. Figure 9 illustrates three patterns of payroll outflows that include large sustained gains or losses. A small business that
hires a single employee who stays with the firm might have a pattern of payroll outflows consistent with the first graph in Figure 9.
Likewise, a small business that loses a single employee without replacing her might have a pattern of payroll outflows consistent with
the second graph in Figure 9. A firm that has a combination of sustained gains and losses might have a pattern of payroll outflows
consistent with the last graph.
Figure 10: Illustrative Examples of Spikes and Dips
5 6 7
Note: We define a full-time equivalent (FTE) as a payroll outflow equivalent to the mean monthly wages per employee for small firms in the same 6-digit NAICS industry as a firm
in our sample.
FTEs
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
0
1
2
3
4
5
6
Dips
FTEs
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
0
1
2
3
4
5
6
Spikes and dips
FTEs
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
0
1
2
3
4
5
6
Spikes
The remaining small businesses in our sample had at least one large change greater
than one FTE that was immediately reversed in the following month—a spike or
a dip.8
The three examples in Figure 10 illustrate these patterns of payroll
outflows. The first example illustrates a spike—a gain of at least one estimated
FTE followed by a similarly large decrease in the next month. The second
example illustrates a dip—a loss of at least one estimated FTE followed by
a similarly large increase in payroll outflows in the next month. The last
example illustrates a combination of spikes and dips. A one-time bonus
payment by a small business to one or more employees could appear as a
spike, while a completely missed payroll payment would appear as a dip.
This map of payroll volatility types gives us a framework with which to
categorize the kinds of payroll volatility that small businesses in our sample
encountered over our study period, as shown in Figure 11.
A majority of small
businesses experienced
changes in payroll outflows
consistent with job gains or
losses, or spikes and dips
in payroll outflows.

Findings
16
Figure 11: 61.8 percent of small employer businesses experienced unstable payroll and employment volatility from job
gains or losses, or from spikes and dips in outflows
Small changes1
Sustained gains2
3
4
5
6
7
Sustained losses
Gains and losses
Dips
Spikes and dips
Spikes
61.8%
38.2%
8.5%
5.6%
11.4%
11.5%
7.4%
17.4%
Stable
payroll
Unstable
payroll
38.2%
We found that 38.2 percent of small businesses experienced only small changes in payroll outflows. In contrast, a significant
majority of small businesses—61.8 percent—experienced changes in payroll outflows consistent with different combinations of
job gains or losses, or spikes and dips in payroll payments, indicating some measure of employment changes that would detract
from the stability of a small business. 8.5 percent of firms experienced sustained gains. While this may correspond to healthy job
growth, the time and effort spent identifying and onboarding a single full-time employee can still be meaningfully disruptive to
a business with only two or three other employees. In addition, a total of 5.6 percent of small businesses experienced sustained
losses. Like a new hire, losing a single employee can correspond to a substantial disruption in cash flow for a very small business,
particularly if the job loss induces a loss in revenue. An even larger share of small businesses—11.4 percent—experienced both
large sustained increases and sustained decreases over the nine-month study period. Whether gains and losses are expected
due to known seasonality or correspond to unexpected turnover, frequent increases and decreases in employees can pose both
operational and cash flow challenges to small businesses.
In our sample, 11.5 percent of the firms experienced one or more spikes, 7.4 percent experienced one or more dips, and 17.4 percent
experienced a combination of spikes and dips. For larger firms in particular, this pattern could also correspond to short-term changes
at the FTE level—for instance, when a small business is unable to quickly replace a worker who unexpectedly leaves, or when a new
employee overlaps for a month with the person she was brought in to replace.
Notably, month-to-month changes in payroll outflows did not correspond to month-to-month changes in cash inflows.9
Across our
sample, in a given month, payroll outflows only correlated with total inflows at 0.13. This suggests that our observed patterns of
volatility are not driven by small business employers who ramp employment up and down in response to predictable or expected
changes in revenue.

Findings
17
The seven patterns of payroll volatility we describe above help to substantively differentiate the ways in which small employer
businesses experience payroll outflows. As noted above, volatile changes in payroll outflows can adversely affect a small business,
independently of whether its payroll grows or declines at a given rate on average. To compare the amount of payroll volatility
experienced by one small business to another, we now develop a single measure of payroll volatility.
Figure 12: Different Types of Volatility Correspond to Different Amounts of Volatility around Baseline Growth
Small changes1 4 Gains and losses 7 Spikes and dips
This hypothetical ﬁrm has
small changes that correspond to
volatility of 7.2%, which places it at the
25th percentile
gains and losses that correspond to
Median
FTEs
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
0
1
2
3
4
5
6
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
0
1
2
3
4
5
6
PayrollGrowthRate
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
-40%
-20%
0%
20%
40%
60%
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
-40%
-20%
0%
20%
40%
60%
spikes and dips that correspond to
75th percentile
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
0
1
2
3
4
5
6
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct-40%
-20%
0%
20%
40%
60%
To provide an intuition for our proposed measure, the top panel of Figure 12 reprises the payroll outflows associated with three of the
volatility type examples presented in Figures 8 through 10. In each case, the hypothetical business has payroll outflows equivalent to
4 FTEs in February, and payroll outflows of 4.7 FTEs in October—corresponding to annualized payroll growth of 24 percent. The black
dotted line in each graph illustrates the progression of payroll payments each firm would have paid had it experienced perfectly
stable payroll growth of 2 percent per month or 24 percent per year.
Finding
Four
The typical small employer business experienced substantial
volatility in payroll outflows, and volatility was highest for younger
small employer businesses.

Findings
18
The main difference between the three hypothetical firms is their experienced month-to-month changes in payroll outflows around
the underlying annualized growth rate depicted by the black dotted line. Intuitively, it appears that the firm with only small changes
has less volatile payroll outflows than the firm with combined sustained gains and losses, which in turn has less volatile outflows than
the firm with a combination of spikes and dips. The three graphs at the bottom of Figure 12 make this intuition explicit by depicting
the month-to-month growth rates of payroll outflows. In fact, the firm with only small changes has the least variability, with month-
to-month growth rates ranging from -7.8 percent to 9.5 percent. The firm with combined sustained gains and losses has somewhat
higher variability, with month-to-month growth rates ranging from -21.9 percent to 26.3 percent. Finally, the firm with both spikes
and dips has the highest variability, with month-to-month growth rates ranging from -25.9 percent to 56.3 percent. Notably, even
the firm with only small payroll outflow changes has growth rates that diverge substantially from the 2 percent month-to-month rate
corresponding to even growth.
With these examples in mind, we define the payroll volatility of a firm as the variation in its month-to-month growth rates, measured
as the standard deviation in monthly growth rates.10
Figure 13 illustrates the distribution of payroll volatility across our sample.
Figure 13: The Median Small Employer Business Experiences Significant Payroll Volatility
25th percentile
7.2%
Median
13.8%
75th percentile
27.2%
Distribution of payroll volatility
0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50%
0.0%
0.5%
1.0%
1.5%
2.0%
2.5%
3.0%
Payroll volatility Source: JPMorgan Chase Institute

Findings
19
A large majority of small businesses do not experience constant or smoothly growing payroll, but rather see payroll levels and
growth rates that swing substantially from one payroll period to the next. Small business payroll very rarely grows smoothly over
the course of a year, consistent with the distribution we found in our qualitative typology. We found that only 1.3 percent of small
businesses had zero payroll volatility (precisely the same growth rate each payroll period over the 9 non-holiday months of 2015),
and only 3.3 percent of small businesses had volatility less than one percent.
In contrast, we found that small business payroll volatility was consistent with the stylized distribution illustrated in Figure 12. Half
of small businesses experienced payroll volatility of 13.8 percent or greater—the same level of payroll volatility illustrated in the
middle panel. A quarter of small businesses experienced higher payroll volatility than that depicted in the right panel, and a quarter
experienced payroll volatility less significant than that depicted in the left panel.
Differences in payroll volatility by business age
Younger businesses were most likely to have volatile payroll outflows. Figure 14 shows the median payroll volatility for firms of
different ages in our sample. Payroll volatility was substantially higher for firms less than two years old. We found that the median
small business in its first year experienced payroll volatility of 17.5 percent, higher than the overall sample median payroll volatility
of 13.8 percent, and much higher than the median payroll volatility of a ten-year-old small business of only 11.9 percent.
Figure 14: Payroll Volatility Declines with Age
Medianpayrollvolatility
Median payroll volatility by age
17.5%
15.6%
14.9%
14.3%
13.6% 13.8%
13.2%
13.8%
13.5% 13.4%
11.9%
<1 1 2 3 4 5 6 7 8 9 10
Age in years

Findings
20
Finally, we explored the relationship between the seven substantive types of payroll volatility we identified earlier and small business
cash liquidity. We summarize this relationship in Figure 15. The small businesses with the most stable payroll had substantially more
cash liquidity than those with larger month-to-month changes. Small businesses with no large changes in payroll had relatively
high cash liquidity—the median business in this group carried 19 cash buffer days. The median small business among those that
only experienced a spike carried slightly more cash buffer days at 20, consistent with the view that these spikes might represent
predictable payments corresponding to increases in revenue. In contrast, the median small business in the group that experienced
combined larger gains and losses only had 16 cash buffer days. The median small business among those that experienced dips
without spikes carried only 15 cash buffer days. These small businesses had the least cash liquidity, and would as such be the most
exposed to any adverse conditions implied by this pattern of payroll changes.
Figure 15: Small Employer Businesses with Dips and Combined Gains/Losses Held the Fewest Cash Buffer Days
Note: Cash buffer days are the number of days of cash outflows a business could pay out of its cash balance if its inflows were to stop. We estimate cash buffer days for a business by
computing the ratio of its average daily cash balance to its average daily cash outflows.
Median cash buffer days by payroll volatility type
15 DAYS
16 DAYS
16 DAYS
17 DAYS
17 DAYS
18 DAYS
19 DAYS
20 DAYS
Dips
Combined sustained
gains and losses
Sustained gains
Both spikes
and dips
Sustained losses
All employer
small businesses
Small changes
Spikes
The volatility types that correspond to changes greater than a full-time employee may reflect meaningful levels of volatility for the
small employer businesses in our sample. We compared the minimum observed daily cash balance for each firm in our sample to
the average payroll for firms in its industry. We found that 47 percent of employer small businesses had at least one day with a cash
balance lower than a semi-monthly paycheck for a single employee and that 37 percent had at least one day with a cash balance
lower than a weekly paycheck. In combination with the low correlation between payroll and cash inflows, this suggests that many
small employer businesses do not always have the cash liquidity to manage volatility from employment expenses.
Finding
Five
Small businesses with more volatile payroll patterns tended to have
fewer cash buffer days.

21
Small businesses are responsible for approximately half of all job creation in the United States and are therefore a critical element of the
US economy. This report provides a new lens on typical small business payroll outflows, their growth, and their volatility. We summarize
key conclusions and implications here:
• New small businesses create new net job; existing small businesses do not. While policy makers have historically focused
on the contributions of small businesses to job creation (Birch, 1981), recent research has emphasized the impact of young firms
on net job creation (Haltiwanger, et al., 2013; Decker, et al., 2014). In fact, after their first year of employment, existing small
businesses lose more jobs than they create, principally through firm failure. For every 100 small business jobs that existed
in 2013, new small businesses created 5.6 new jobs, while existing small businesses lost 3.9 jobs—mostly due to losses from
the exit of these small businesses. Policy makers, advocates, and private-sector partners should focus on the incentives and
sustainability of the new small businesses that create these jobs. This is especially concerning in light of the overall decline in
startup rates, which have fallen from 17.1 percent in 1977 to 10 percent in 2014.11
• Employment-related costs are a substantial share of expenses for a typical small business. Job creation is a central
element of economic growth, but it requires small business owners to make significant investments. This report focused on
the amounts employers spend on their employees' take-home pay—these expenses alone represent 18 percent of all employer
outflows, and are higher than 25 percent in many industries. Moreover, after adjusting for likely tax payments, we found that
these employment costs likely account for 22 percent of outflows for most employers and over 30 percent in many industries.
• In addition to generating a significant share of small business expenses, employment also is a source of substantial
cash flow volatility and impacts liquidity. In Cash is King: Flows, Balances, and Buffer Days, we found that the median small
business only has enough cash on hand to weather 27 days without any inflows. Employer small businesses have an even
smaller cash buffer of just 18 days. Those employer small businesses that suffer from large dips or large gains and losses in
payroll have even fewer cash buffer days in reserve.
• Small and especially young businesses are particularly vulnerable to payroll volatility. Prior research has illustrated
the significant role that young rather than small businesses play in creating jobs in the US economy (Haltiwanger, et al., 2013).
We observe a similar pattern of growth among young businesses. The median small business less than two years in age sees
faster payroll growth than the median small business over two years in age, suggesting that younger small businesses that
survive a full year are creating new jobs by hiring new employees, creating better jobs by offering more hours to their existing
employees, or paying their employees higher wages or salaries.
While these young small businesses play a key role in job creation, they are also quite vulnerable. Nearly
one-third of businesses exit the market within their first two years.12
Job losses due to firm exit
detract significantly from the net job creation rate, particularly among young and small
firms. These two factors combine and contribute to the consistent net job destruction
by existing small businesses.
Our findings provide a preliminary lens that reconciles job creation by young
businesses with their instability and contributions to job loss. While many young
small businesses have growing payroll outflows consistent with job creation,
young small businesses also have the most volatile payroll growth. Future
research should explore whether the very factors that contribute to job growth
among young and small firms also contribute to volatility and whether these
volatile cash flows combine with limited cash liquidity to contribute to firm
failure.Armedwiththisinformation,policymakers,advocates,andprivate-sector
partners can take care to ensure that policies aimed at supporting small business
job creation do not inadvertently contribute to the failure of young small businesses.
While young small
businesses play a key role
in job creation, they are
also quite vulnerable.
Conclusion and Implications

Implications and Conclusion
22
• Payroll volatility has adverse implications for small business employees as well as small business owners. This report
offers new data and insights on the extent of payroll volatility among small businesses and the impact of this volatility on small
business owners. However, payroll volatility also has the potential to significantly impact small businesses employees. The
small business sector employs nearly half of the US workforce, which exposes a significant fraction of US households to the
economic outcomes of small businesses. In Paychecks, Paydays, and the Online Platform Economy, the JPMorgan Chase Institute
found that 53 percent of income volatility was derived from labor sources and that 86 percent of variation in take-home-pay
came from variation when a worker stayed with the same employer (Farrell and Greig, 2016). For those workers employed by
small businesses, the results presented here provide an employer-side lens on this same phenomenon. To the extent that policy
makers can design interventions that minimize payroll volatility for small businesses, they can also limit the take-home-pay
volatility of the small business employees.
• Policy makers also frequently face a tension between improving the conditions and wages of employees and imposing
costs on their employers. Given that payroll expenses are a large share of outflows for small employer business owners, policy
makers should take special care to ensure that these rules are tailored to meet the specific needs of small businesses. With the
median employer small business having only 18 cash buffer days on hand, these businesses are already living on a less than
month-to-month basis. Increasing the cost of employment could lead many of them to face the costly choice between cutting
payroll expenses or increasing their vulnerability to liquidity shocks.

23
In this report, the JPMorgan Chase Institute seeks to inform the public debate on the financial lives of employer small businesses in
the US. To draw conclusions about payroll outcomes, we adapted the firm’s internal data on US small business accounts into a secure
groundbreaking data asset. As the first financial institution to channel this wealth of information for the benefit of the public good,
JPMorgan Chase put strong guardrails and strict privacy policy protocols in place to protect personal information throughout the
creation and analysis of this data asset.
Data Asset
Data Privacy
The JPMorgan Chase Institute has adopted rigorous security protocols and checks and balances to ensure all customer
data are kept confidential and secure. Our strict protocols are informed by statistical standards employed by
government agencies and our work with technology, data privacy, and security experts who are helping us maintain
industry-leading standards.
There are several key steps the Institute takes to ensure customer data are safe, secure and anonymous:
• Before the Institute receives the data, all unique identifiable information—including names, account numbers,
addresses, dates of birth, Social Security numbers, and Employer Identification Numbers (EIN)—is removed.
• The Institute has put in place privacy protocols for its researchers, including requiring them to undergo rigorous
background checks and enter into strict confidentiality agreements. Researchers are contractually obligated to use
the data solely for approved research and are contractually obligated not to re-identify any individual represented
in the data.
• The Institute does not allow the publication of any information about an individual consumer or business. Any data
point included in any publication based on the Institute’s data may only reflect aggregate information.
• The data are stored on a secure server and can be accessed only under strict security procedures. The data cannot
be exported outside of JPMorgan Chase’s systems. The data are stored on systems that prevent them from being
exported to other drives or sent to outside email addresses. These systems comply with all JPMorgan Chase
Information Technology Risk Management requirements for the monitoring and security of data.
The Institute provides valuable insights to policy makers, businesses, and nonprofit leaders. But these insights cannot
come at the expense of customer privacy. We take precautions to ensure the confidence and security of our account
holders’ private information.

Data Asset
24
Constructing our samples
Payroll in 2015 Non-Holiday Months – We chose to focus exclusively on transaction data from the calendar year 2015. This allowed
us to compare the payroll characteristics of a set of small businesses that faced a largely stable macroeconomic environment.
Moreover, many small businesses experience substantial changes in their payroll outflows during the holiday season and at the
change of a calendar year. In particular, many businesses may pay bonuses or have other payments during these months that are not
typical of their pattern of payroll during the rest of the year. In this report, we chose to focus on these months in order to characterize
the volatility that comes from more typical periods of business. To the extent that small businesses experience substantial changes in
payroll during the holiday and change-of-year months of November, December, and January, the findings we report here likely reflect
a conservative view of the payroll volatility these small businesses face. Moreover, by focusing on these months, we align with our
earlier work on small business cash liquidity.
Identifying Core Metropolitan Operating Employer Small Businesses – From the universe of business customers that had active
deposit accounts in 2015 in our 12 identified industries, we selected a sample of over 45,000 customers for which we were able to
identify electronic payroll outflows in each month among a set of accounts that likely reflects the operating activity of the business.
Specifically, we applied six additional screening criteria:
• Each business must be associated with a single geographic location in a metro area and a single industry for
each observed month.13
• Each business must have both a cash inflow and outflow for each month from February through October 2015.
• For at least five of these nine months, the business must have at least $500 in outflows and 10 combined inflows and outflows.
• The business must never exceed a combined balance of $20 million across all of its accounts.
• The business must have continuously identifiable daily balances for each posting day from February through October 2015.
• The business must have observed electronic payroll outflows indicating at least one and less than 500 employees for each
payroll period.
In combination, these criteria allow us to identify a population of employer small businesses for which we have a window on the
payroll outflows that flow from their Chase Business Banking accounts. In particular, these criteria are intended to screen out larger
businesses that might have deposit accounts across multiple banks. While some businesses may engage in cash transactions that do
not flow through their bank accounts, our sample criteria identify a set of businesses that are likely to substantially transact through
their accounts.
Representativeness of our sample
The size of our subsample aligns with public data from the Census Bureau, as shown in Figure 16. In 2013, the Census Non-Employer
Statistics identified 23 million non-employer businesses, while the Census Statistics of US Businesses only identifies 5.8 million
firms with any employees at all. Moreover, over 60 percent of these employer small businesses (3.6 million) have fewer than 5
employees, while fewer than 2.2 million businesses have 5 or more employees. In total, 7.6 percent of Census firms have more than
five employees. Out of a sample of approximately 600,000 total operating small businesses, we were able to identify over 45,000
with payroll outflows, or 7.6 percent. In as much as very small businesses with fewer than 5 employees might be less likely to use
electronic payroll services, the 7.6 percent of employer firms in our sample is comparable to the 7.6 percent of firms with 5 or more
employees in the Census sample.

Data Asset
25
Figure 16: Payroll Share of JPMCI Sample is Similar to Comparable Employer Share from Census
Sources: JPMorgan Chase Institute; US Census Bureau, Statistics of US Businesses and Nonemployer Statistics, 2013
Firm share in JPMCI sample
No identiﬁed payroll
Identiﬁed
payroll
Firm share of all US businesses
92.4%
7.6%
79.9%
12.4%
7.7%
Nonemployer
Fewer than 5
employees
5 or more
employees
Industry Mix – Figure 17 compares the share of our small business sample in our 12 identified industries to a benchmark of small
businesses with fewer than 500 employees in the same 12 industries. With some exceptions, our sample approximates these industry
shares closely. Notably, small employer businesses in the Health Care Services industry comprise 22 percent of our data asset but
only 12 percent of small employer businesses in the US. In contrast, small employer businesses in the Construction industry only
comprise 9 percent of our data asset, but 15 percent of small employer businesses in the US.
Figure 17: Industry Composition of JPMCI Employer Small Business Data Asset
Industry JPMCI Small Employer Business Sample Share US Employer Small Business Share
Construction 9% 15%
Health Care Services 22% 12%
High-Tech Manufacturing14
1% 0%
High-Tech Services 5% 3%
Metal & Machinery 3% 2%
Other Professional Services 14% 14%
Personal Services 7% 4%
Real Estate 5% 6%
Repair & Maintenance 7% 9%
Restaurants 10% 11%
Retail 12% 16%
Wholesalers 7% 7%
Source: JPMorgan Chase Institute; US Census, Statistics of US Businesses, 2013

Data Asset
26
Regional Distribution – Guided by the Chase footprint, we focus on small businesses in Metropolitan Statistical Areas (MSAs). MSAs
consist of core urban areas with a population of 50,000 or more as well as any adjacent counties that have a high degree of social
and economic integration with the urban core, as measured by work commuting. While some of these adjacent counties may be rural
in nature, our focus on MSAs implies a focus on mostly non-rural areas.
Figure 18 compares the share of our small businesses to the share of all small businesses in the US by region. The figure identifies
regions in which we observe significantly larger or smaller shares of employer small businesses than are observed by the Census. The
regional differences we observe largely reflect the Chase branch footprint across the US. Our sample offers large numbers of small
businesses across all four regions, with stronger coverage in the Northeast and West, and less coverage in the South.
Figure 18: JPMCI Small Businesses are Well-Represented Across US Regions
Sources: JPMorgan Chase Institute; US Census, Statistics of US Businesses, 2013
Regional distribution of JPMCI and Census samples
22%
24% 24%
30%
21%
20%
34%
24%
JPMCI Small Employer Business Sample Census Small Employer Business Sample
Midwest Northeast South West

27
Methodology
Defining and measuring payroll outflows, growth, and volatility
Within this report, we define payroll as the outflow that small businesses pay directly to employees. We identify these outflows
through payments from the small business to electronic payroll processors who then distribute the funds to employees on behalf of
the small business. This provides a lens on the funds that go directly to the employees’ paychecks; we do not measure payroll-related
expenses such as taxes and benefits.
We also followed an approach intended to remove calendar effects from the analysis. In particular, we sought to avoid the impact of
“five Friday” months—months that contain five Fridays instead of four. If a small business pays its employees every week or every
two weeks, we would observe higher aggregate payroll outflows in months with five Fridays than those with four. This would create
changes in month-to-month growth rates that would reflect a misalignment of the calendar with the payroll cycle of the business
that might not be meaningful to the economics of the business itself. To avoid this effect, when conducting this analysis, we split our
firms into two groups: those who pay employees on a monthly or semi-monthly basis, and those who pay employees on a weekly or
biweekly basis. We identified these groups as follows:
• Firms who paid employees on a monthly or semi-monthly basis should make these payments around the same dates of the
month (for instance, the 15th and the 30th). We classify a firm as having monthly or semimonthly payments if we observe 65%
or more of the dollar value of its payroll outflows paid out on the same 4 dates within each month. This group represents 26.3%
of our sample and 31.1% of all employer small businesses, according to the Bureau of Labor Statistics.15
• Firms who paid employees on a weekly or biweekly basis should make these payments around the same time each week (for
instance, each Friday). We classify a firm as having weekly or biweekly payments if we observe 85% or more of the dollar value
of its payroll outflows paid out on the same 2 days of the week each week. This group represents 73.7% of our sample and
68.9% of all employer small businesses, according to the Bureau of Labor Statistics.15
Payroll Outflows
For the firms we identified as paying employees on a monthly or semi-monthly, we divided the calendar into nine monthly periods
from February to October 2015, and measured payroll outflows pi,t as the sum of all individual payroll outflows for a firm i that
occurred in a month t. For firms we identified as paying employees on a weekly or biweekly basis, we divided the calendar into a
series of 28-day periods, such that the first began on Monday, February 16, 2015 and ended Sunday, March 15, 2015, the second
began on Monday, March 16, 2015 and ended Sunday, April 12th, and the last began Monday, September 28, 2015 and ended on
Sunday, October 25, 2015. This produced nine 28-day periods that also occurred within the nine non-holiday months of the year, and
guaranteed that each time period included exactly four Fridays (or alternative payroll day-of-week). For these firms, we measured
payroll outflows pi,t as the sum of all individual payroll outflows for a firm i that occurred in a 28-day period t.

Methodology
28
Payroll Growth
Our observation window for payroll outflows for firms that paid employees on a monthly or semi-monthly basis extended from
February 1 to October 31, while our observation window for firms that paid employees on a weekly or semi-weekly basis only extended
from February 16 to October 25. To ensure that this difference in observation windows did not cause us to differently estimate payroll
growth for these two groups of firms, and to facilitate comparison to other annual growth rate measures, we estimated an annualized
growth rate for both. To facilitate this and our volatility measure, we first measure annualized logarithmic period-to-period payroll
growth rates ppgt,i for each firm i in each period t. For firms that pay employees on a monthly or semi-monthly basis, we scale each
month-to-month logarithmic growth rate by 12 to compute an annualized measure:
ppgi,t = (ln—) x 12.Pt
Pt−1
For firms that pay on a weekly or biweekly basis, we scale the logarithmic growth rate by the number of 28-day periods in the average
365.25 day year:
ppgi,t = (ln—) x—.Pt
Pt−1
365.25
28
To compute our reported annualized payroll growth measure pgi for each firm, we exponentiate the average period-to-period
annualized growth rate for each firm across our nine payroll periods:
ppgi = e—.
Σtppgi,t
9
Payroll Volatility
Our quantitative measure of payroll volatility is based on the volatility of growth rates around the average growth rate pgi for a firm
in our sample. Specifically, we divide the annualized logarithmic period-to-period payroll growth rates ppgt,i by 12 to create a set of
monthly logarithmic period-to-period payroll growth rates. We then exponentiate the standard deviation of those monthly logarithmic
growth rates to yield a measure similar to the monthly percent variance in growth rates. We compute this measure pvi as:
pvi = estd(ppgi,t /12)
.

29
Appendix:
Payroll Growth and Volatility by Industry and Metro Area
Figure 19: Payroll Growth Varies Substantially Across and Within Industries
Figure 20: Payroll Volatility Varies Substantially Across and Within Industries
Annualizedpayrollgrowth
Payroll growth by industry
High-Tech
Manufacturing
Metal&
Machinery
RealEstate
Wholesalers
Retail
Other
Professional
Services
Personal
Services
High-Tech
Services
AllSmall
Businesses
HealthCare
Services
Restaurants
Repair&
Maintenance
Construction
33%
28%
34% 35%
42% 40% 41%
46%
43%
36%
50% 49%
77%
-13% -14%
-9% -9% -10% -12% -12% -12% -10% -8%
-13%
-9% -7%
4% 4% 6% 7% 7% 7% 7% 8% 9% 9% 10% 11%
20%
75th
percentile
25th
percentile
Median
0%
Payrollvolatility
Payroll volatility by industry
23%
27%
25%
26% 27%
26%
27% 27%
26% 27%
27%
30%
31%
6%
6% 6%
7% 6% 7% 7% 7% 8% 8% 7% 7%
10%
12% 12% 12%
13% 13% 14% 14% 14% 14% 14% 14% 14%
18%
Metal&
Machinery
High-Tech
Manufacturing
RealEstate
HealthCare
Services
Wholesalers
Retail
Restaurants
AllSmall
Businesses
Repair&
Maintenance
Personal
Services
High-Tech
Services
Other
Professional
Services
Construction
75th
percentile
25th
percentile
Median

Small Business Data Dashboard
30
Figure 21: Payroll Growth by Metropolitan Area
Figure 22: Payroll Volatility by Metropolitan Area
Annualized payroll growth rate by metropolitan area
SanDiego,CA
Phoenix,AZ
Miami,FL
NewOrleans,LA
Houston,TX
NewYork,NY
SaltLakeCity,UT
Milwaukee,WI
Austin,TX
Orlando,FL
LosAngeles,CA
Chicago,IL
Tampa,FL
SanJose,CA
SanFrancisco,CA
Atlanta,GA
Detroit,MI
Portland,OR
Denver,CO
Seattle,WA
Columbus,OH
Dallas,TX
LasVegas,NV
Louisville,KY
4.8%
5.0%
5.6%
6.7%
7.2%
7.4%
7.7%
8.4%
8.6%
8.9%
9.3%
9.7%
9.8%
10.1%
10.4%
10.4%
10.8%
10.9%
11.0%
11.0%
11.2%
13.1%
13.8%
19.1%
Payroll volatility by metropolitan area
12.6%
12.7%
13.1%
13.1%
13.4%
13.5%
13.6%
13.7%
13.7%
13.8%
13.9%
14.1%
14.2%
14.3%
14.6%
14.6%
14.7%
14.9%
15.2%
15.2%
15.3%
15.4%
16.0%
17.2%
SaltLakeCity,UT
NewYork,NY
Louisville,KY
Columbus,OH
NewOrleans,LA
Milwaukee,WI
Phoenix,AZ
SanJose,CA
Austin,TX
Detroit,MI
Miami,FL
SanDiego,CA
Tampa,FL
Chicago,IL
LosAngeles,CA
Seattle,WA
Houston,TX
Dallas,TX
Portland,OR
Denver,CO
SanFrancisco,CA
Atlanta,GA
Orlando,FL
LasVegas,NV

31
References
Birch, David L. 1981. “Who Creates Jobs?” Public Interest 65. 3-14.
Burgess, Matt. 2014. “How Frequently do Private Businesses Pay Workers?” Beyond the Numbers: Pay and Benefits 3.
http://www.bls.gov/opub/btn/volume-3/how-frequently-do-private-businesses-pay-workers.htm
Davis, Steven J. and John Haltiwanger. 1992. “Gross Job Creation, Gross Job Destruction, and Employment Reallocation.” Quarterly Journal
of Economics 107: 819-863. doi:10.2307/2118365
Davis, Steven J., Haltiwanger, John, and Scott Schuh. 1996. “Small Business and Job Creation: Dissecting the Myth and Reassessing the
Facts.” Small Business Economics 8: 297-315. doi: 10.1007/BF00393278
Decker, Ryan, Haltiwanger, John, Jarmin, Ron, and Javier Miranda. 2014. “The Role of Entrepreneurship in US Job Creation and Economic
Dynamism.” Journal of Economic Perspectives 28: 3-24. doi: 10.1257/jep.28.3.3
Farrell, Diana and Greig, Fiona. 2016. “Paychecks, Paydays, and the Online Platform Economy: Big Data on Income Volatility.” JPMorgan
Chase Institute. https://www.jpmorganchase.com/corporate/institute/report-paychecks-paydays-and-the-online-platform-economy.htm
Farrell, Diana and Wheat, Christopher. 2016. “Cash is King: Flows, Balances and Buffer Days, Evidence from 600,000 Small Businesses.”
JPMorgan Chase Institute. https://www.jpmorganchase.com/corporate/institute/report-cash-flows-balances-and-buffer-days.htm
Haltiwanger, John, Jarmin, Ron S., and Javier Miranda, 2013. “Who Creates Jobs? Small versus Large versus Young.” Review of Economics
and Statistics 95: 347-367. doi: 10.1162/REST_a_00288
Suggested citation
Farrell, Diana and Wheat, Christopher. 2017. “Making Payroll: Big Data on Payroll Growth and Volatility.” JPMorgan Chase Institute.
https://www.jpmorganchase.com/corporate/institute/making-payroll.htm

32
1 Research attempting to identify the specific impact of small businesses on job creation (Davis and Haltiwanger, 1992; Davis et al., 1996)
differentiates the gross job creation process by separately identifying job creation and job destruction. Net job creation refers to jobs created
less jobs destroyed.
2 We calculated annual full-time equivalent wages for a firm by dividing the total annual payroll for its 6-digit NAICS industry by the total number
of employees in that industry. We calculated monthly full-time equivalent wages for a firm by dividing its annual full-time equivalent wages by
12. We drew annual payroll and employee numbers from the US Census Statistics of US Businesses data.
3 The relatively large share of firms that see an increase equivalent to two or more FTEs is driven in part by firms with higher numbers of
employees. Adding two or more employees at a larger firm might still correspond to a relatively low payroll growth rate. Among firms with
fewer than 10 estimated employees, we find only 14 percent that add two or more employees. In contrast, 12 percent of firms with fewer than
10 estimated employees add one to two additional employees.
4 We measure the age of a business by identifying the opening date of the oldest business deposit account associated with the customer.
5 Existing firms with more than 500 employees produced 3.8 new jobs for every 100 existing jobs, and lost 2.1 jobs due to firm exit, resulting in
a net job creation rate of 1.7 percent for existing firms. New firms with more than 500 employees created 0.2 new jobs for each of these 100
existing jobs. Overall, larger firms produced net jobs at a rate of 1.9 percent. The non-zero rate of job creation by new firms with more than
500 employees results from the very small number of new legal entity large firms in a given year. For example, of the 403,902 firms that first
reported employment in 2014, 72 had 500 or more employees.
6 In this study, we separate firms that pay payroll on a weekly or bi-weekly basis from those that pay on a semi-monthly or monthly basis in order
to avoid payroll volatility attributable to calendar effects. We report all findings in terms of implied monthly rates. See Methodology section
for further details on this process.
7 This pattern also could capture businesses that gain or lose a new employee who earns less than the average monthly wage for the industry or
who joined/left the firm in the middle of the month.
8 Firms we classify as having a dip and/or a spike may also have large sustained job gains and/or losses.
9 Cash inflows refer to credit transactions into any business deposit of savings account, such as revenues, owner transfers into the account from
private savings, loan funding, or tax rebates.
10 Specifically, we measure payroll volatility by first calculating the standard deviation of the natural logarithm of the ratio of payroll outflows
in consecutive months or 28-day periods. We then exponentiate this standard deviation to produce a number that roughly corresponds to the
standard deviation of month-to-month growth rates in percent terms. See Methodology section for further details.
11 We define annual startup rates as the establishment entry rate published in the US Census Bureau, Business Dynamics Statistics series.
12 See Bureau of Labor Statistics Business Employment Dynamics, establishment survival data: http://www.bls.gov/bdm/entrepreneurship/
entrepreneurship.htm.
13 We identify a business as being in a metropolitan area if its zip code overlaps with a Census Metropolitan Statistical Area (rather than a
Micropolitan Statistical Area).
14 Zero value due to rounding.
15 Burgess (2014) identifies shares of private employers who pay employees on a weekly, bi-weekly, semi-monthly and monthly basis.
Endnotes

This material is a product of JPMorgan Chase Institute and is provided to you solely for general information purposes.
Unless otherwise specifically stated, any views or opinions expressed herein are solely those of the authors listed and may differ
from the views and opinions expressed by J.P. Morgan Securities LLC (JPMS) Research Department or other departments or divisions
of JPMorgan Chase & Co. or its affiliates. This material is not a product of the Research Department of JPMS. Information has
been obtained from sources believed to be reliable, but JPMorgan Chase & Co. or its affiliates and/or subsidiaries (collectively
J.P. Morgan) do not warrant its completeness or accuracy. Opinions and estimates constitute our judgment as of the date of this
material and are subject to change without notice. The data relied on for this report are based on past transactions and may not be
indicative of future results. The opinion herein should not be construed as an individual recommendation for any particular client
and is not intended as recommendations of particular securities, financial instruments, or strategies for a particular client. This
material does not constitute a solicitation or offer in any jurisdiction where such a solicitation is unlawful.
©2017 JPMorgan Chase & Co. All rights reserved. This publication or any portion hereof may not be reprinted, sold, or redistributed
without the written consent of J.P. Morgan. www.jpmorganchaseinstitute.com

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